Raw Material Costs in Precursor Process Reduced by 5.4%
"Annual Cost Savings of 5.5 Billion Won"
Amber Road, a manufacturing artificial intelligence (AI) solutions company, has demonstrated cost-saving effects by applying its proprietary process optimization system to real-world manufacturing sites.
On December 23, domestic venture capital firm Stonebridge Ventures announced, "Amber Road, a company invested in by Stonebridge Ventures, has applied its AI-based process optimization system to the precursor raw material process of EcoPro Materials, a secondary battery materials company, and confirmed annual cost savings of approximately 5.5 billion won."
The precursor production process at EcoPro Materials is a 24-hour continuous operation that extracts nickel, cobalt, manganese, and other materials. However, component analysis is conducted only three times a day, making it difficult to reflect real-time changes in concentration during the process. As a result, auxiliary materials such as caustic soda and sulfuric acid were being overused by about 22% compared to theoretical values, leading to inefficiency. The related costs amounted to approximately 8 billion won annually and had been regarded as 'unavoidable expenses.'
Amber Road identified the core issue as the difficulty in real-time interpretation of process data and optimal control. To address this, the company implemented its manufacturing AI platform, MinerReport, establishing a real-time component prediction model and an auxiliary material input optimization guidance system. As a result, the input of auxiliary materials was reduced by 5.4% compared to previous levels, and losses from rework due to underuse also decreased, verifying economic benefits of around 5.5 billion won per year.
The speed of implementation is also cited as a strength. By ensuring compatibility with existing systems, incorporating domain knowledge, and establishing operational and management frameworks, Amber Road shortened the typical AI adoption period, which usually takes more than 10 months. This enabled the company to launch multiple pilot projects within three months.
In addition, significant annual financial results-amounting to several billion won-have been confirmed in other projects, such as reducing excess input of ferroalloys in POSCO's steelmaking process, optimizing zinc plating concentration at KG Steel, and optimizing slurry spraying and drying processes. The company is also collaborating with Dongseo Food, LS Mtron, and Boston Consulting Group (BCG), among others.
Industry experts note that, despite the rapid spread of AI technology in manufacturing sites, it has been rare to see immediate improvements in profitability. Therefore, Amber Road's demonstrated results are considered highly significant. This year, Amber Road also received the Grand Prize and the Minister of SMEs and Startups Award at the Public-Private Partnership Open Innovation Integrated Competition.
Amber Road CEO Lim Eonho stated, "The value of AI in manufacturing sites depends on whether it leads to direct profit improvement. We have focused on process optimization AI that addresses core manufacturing challenges such as reducing raw material and energy costs. Going forward, we will continue to contribute to strengthening the competitiveness of the manufacturing industry with AI technologies that can be immediately implemented on site."
Choi Dongyeol, Head of Investment at Stonebridge Ventures, explained, "Amber Road is a startup we directly discovered, and we decided to invest after seeing its scalable technology, which can be expanded to various manufacturing fields."
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